Precise Landing of Autonomous Aerial Vehicles Using Vector Fields

Gonçalves, Vinícius Mariano; McLaughlin, Ryan; Pereira, Guilherme A. S.

doi:10.1109/lra.2020.2994485

Cited by 21 publications

(12 citation statements)

References 20 publications

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“…2019 ; Gonçalves et al. 2020 ). Many landing solutions using planar markers change the flight behavior to use only ArUco localization when in range instead of combining information from different sources.…”

Section: Related Workmentioning

confidence: 99%

“…With a focus on the landing process, Gonçalves et al. ( 2020 ) present a control method based on vector fields for autonomous landing in a fixed platform. They use visual feedback of a marker on the target to estimate the relative distance and compute a velocity vector field to follow a path to landing.…”

Section: Related Workmentioning

confidence: 99%

“…Visual localization methods could aid in locating the landing area accurately, even in partially cluttered scenarios, using equipment already deployed in the platform, for instance, RGB cameras. Planar markers such as the ArUco (Garrido-Jurado et al 2014) can generate robust pose estimation from heights up to 30 m and are a feasible solution for drone landing (Wubben et al 2019;Marut et al 2019;Gonçalves et al 2020). Many landing solutions using planar markers change the flight behavior to use only ArUco localization when in range instead of combining information from different sources.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Autonomous Navigation System for a Delivery Drone

Miranda

Rezende

Rocha

et al. 2021

J Control Autom Electr Syst

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The use of delivery services is an increasing trend worldwide, further enhanced by the COVID pandemic. In this context, drone delivery systems are of great interest as they may allow for faster and cheaper deliveries. This paper presented a navigation system that makes feasible the delivery of parcels with autonomous drones. The system generates a path between a start and a final point and controls the drone to follow this path based on its localization obtained through GPS, 9DoF IMU, and barometer. In the landing phase, information of poses estimated by a marker (ArUco) detection technique using a camera, ultrawideband (UWB) devices, and the drone’s software estimation are merged by utilizing an extended Kalman filter algorithm to improve the landing precision. A vector field-based method controls the drone to follow the desired path smoothly, reducing vibrations or harsh movements that could harm the transported parcel. Real experiments validate the delivery strategy and allow the evaluation of the performance of the adopted techniques. Preliminary results state the viability of our proposal for autonomous drone delivery.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Autonomous Navigation System for a Delivery Drone

Miranda

Rezende

Rocha

et al. 2021

J Control Autom Electr Syst

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“…An optical-flow-based strategy is proposed in [10] to achieve the landing task of a micro air vehicle by adjusting the controller gains. In [11], another approach is presented for a quadcopter based on the velocity vector field method. While these studies only considered fixing the landing pads on flat platforms, the authors of [12] addressed a robust controller allowing a quadcopter to land on a slope.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Quadcopter Precision Landing Onto a Heaving Platform: New Method and Experiment

et al. 2020

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Nowadays, with the increasing popularity of quadcopter unmanned aerial vehicles in several real-world applications, achieving a fully autonomous quadcopter flight has become an imperative topic investigated in many studies. One of the most pressing issues in such a topic is the precision landing task, which always is devastatingly influenced by the ground effect and external disturbances. In this paper, we present an autonomous quadcopter landing algorithm allowing the vehicle to land robustly and precisely onto a heaving platform. Firstly, a robust control algorithm addressing the altitude flight under the ground effect and external disturbances is derived. We strictly prove the closed-loop system stability by using the Lyapunov theory. Secondly, a landing target state estimator is proposed to provide state estimations of the moving landing target. In addition, we propose a landing procedure to ensure the landing task is achieved safely and reliably. Finally, we use a DJI-F450 drone equipped with an infrared sensor and a laser ranging sensor as the experimental quadcopter platform and conduct experiments to evaluate the performance of our new algorithm in real flight conditions. The experimental results demonstrate the effectiveness of the proposed method. INDEX TERMS Autonomous landing, precision landing, moving target, quadcopter, heaving platform, ship deck, robust control, sliding mode control, disturbance observer.

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“…Commercial solutions, such as the DJI Mavic Pro Precision Landing, proved [89] to be inferior with a position error of 8.76 cm without heading control. On the other hand, Gonçalves et al [90] tested autonomous landing control with vector fields, using nested fiducial markers on a computer vision system, achieving a horizontal landing error of 14 cm. Wang et al [91] was capable of land on a stationary landing pad with a position error smaller than 30 cm.…”

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confidence: 99%

Precision Landing for Low-Maintenance Remote Operations with UAVs

Moreira¹,

Azevedo

Ferreira³

et al. 2021

Drones

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This work proposes a fully integrated ecosystem composed of three main components with a complex goal: to implement an autonomous system with a UAV requiring little to no maintenance and capable of flying autonomously. For this goal, was developed an autonomous UAV, an online platform capable of its management and a landing platform to enclose and charge the UAV after flights. Furthermore, a precision landing algorithm ensures no need for human intervention for long-term operations.

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Precise Landing of Autonomous Aerial Vehicles Using Vector Fields

Cited by 21 publications

References 20 publications

Autonomous Navigation System for a Delivery Drone

Autonomous Navigation System for a Delivery Drone

Autonomous Quadcopter Precision Landing Onto a Heaving Platform: New Method and Experiment

Precision Landing for Low-Maintenance Remote Operations with UAVs

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